Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations31080
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10
DateTime1
Categorical1

Alerts

air_temp is highly overall correlated with clearsky_dhi and 4 other fieldsHigh correlation
clearsky_dhi is highly overall correlated with air_temp and 6 other fieldsHigh correlation
clearsky_ghi is highly overall correlated with air_temp and 6 other fieldsHigh correlation
cloud_opacity is highly overall correlated with clearsky_dhi and 4 other fieldsHigh correlation
dni is highly overall correlated with air_temp and 6 other fieldsHigh correlation
ghi is highly overall correlated with air_temp and 6 other fieldsHigh correlation
hour is highly overall correlated with clearsky_dhi and 4 other fieldsHigh correlation
relative_humidity is highly overall correlated with air_temp and 4 other fieldsHigh correlation
period_end has unique valuesUnique
clearsky_dhi has 14427 (46.4%) zerosZeros
clearsky_ghi has 14424 (46.4%) zerosZeros
cloud_opacity has 559 (1.8%) zerosZeros
dni has 19987 (64.3%) zerosZeros
ghi has 14473 (46.6%) zerosZeros
hour has 1295 (4.2%) zerosZeros

Reproduction

Analysis started2024-07-25 14:38:55.073358
Analysis finished2024-07-25 14:39:03.243305
Duration8.17 seconds
Software versionydata-profiling vv4.9.0
Download configurationconfig.json

Variables

air_temp
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.797394
Minimum22
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:03.292332image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile23
Q125
median26
Q327
95-th percentile28
Maximum31
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5650794
Coefficient of variation (CV)0.060668121
Kurtosis-0.55090953
Mean25.797394
Median Absolute Deviation (MAD)1
Skewness0.22307854
Sum801783
Variance2.4494736
MonotonicityNot monotonic
2024-07-25T09:39:03.382445image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
25 7392
23.8%
26 6686
21.5%
27 5223
16.8%
24 5137
16.5%
28 3471
11.2%
23 1649
 
5.3%
29 1274
 
4.1%
30 155
 
0.5%
22 84
 
0.3%
31 9
 
< 0.1%
ValueCountFrequency (%)
22 84
 
0.3%
23 1649
 
5.3%
24 5137
16.5%
25 7392
23.8%
26 6686
21.5%
27 5223
16.8%
28 3471
11.2%
29 1274
 
4.1%
30 155
 
0.5%
31 9
 
< 0.1%
ValueCountFrequency (%)
31 9
 
< 0.1%
30 155
 
0.5%
29 1274
 
4.1%
28 3471
11.2%
27 5223
16.8%
26 6686
21.5%
25 7392
23.8%
24 5137
16.5%
23 1649
 
5.3%
22 84
 
0.3%

clearsky_dhi
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct273
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.579633
Minimum0
Maximum343
Zeros14427
Zeros (%)46.4%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:03.473893image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q3117
95-th percentile164
Maximum343
Range343
Interquartile range (IQR)117

Descriptive statistics

Standard deviation64.273248
Coefficient of variation (CV)1.1359785
Kurtosis-1.1244892
Mean56.579633
Median Absolute Deviation (MAD)10
Skewness0.57201951
Sum1758495
Variance4131.0504
MonotonicityNot monotonic
2024-07-25T09:39:03.583216image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14427
46.4%
125 199
 
0.6%
117 197
 
0.6%
122 195
 
0.6%
126 193
 
0.6%
121 182
 
0.6%
113 180
 
0.6%
116 180
 
0.6%
135 180
 
0.6%
109 180
 
0.6%
Other values (263) 14967
48.2%
ValueCountFrequency (%)
0 14427
46.4%
1 63
 
0.2%
2 45
 
0.1%
3 171
 
0.6%
4 128
 
0.4%
5 105
 
0.3%
6 105
 
0.3%
7 102
 
0.3%
8 165
 
0.5%
9 144
 
0.5%
ValueCountFrequency (%)
343 1
< 0.1%
337 1
< 0.1%
331 1
< 0.1%
316 1
< 0.1%
314 1
< 0.1%
308 1
< 0.1%
298 1
< 0.1%
294 1
< 0.1%
290 1
< 0.1%
278 1
< 0.1%

clearsky_ghi
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1022
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean284.36075
Minimum0
Maximum1024
Zeros14424
Zeros (%)46.4%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:03.685733image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q3630
95-th percentile937
Maximum1024
Range1024
Interquartile range (IQR)630

Descriptive statistics

Standard deviation359.30817
Coefficient of variation (CV)1.2635646
Kurtosis-1.063813
Mean284.36075
Median Absolute Deviation (MAD)14
Skewness0.77936274
Sum8837932
Variance129102.36
MonotonicityNot monotonic
2024-07-25T09:39:03.789202image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14424
46.4%
4 154
 
0.5%
10 122
 
0.4%
5 107
 
0.3%
11 106
 
0.3%
17 83
 
0.3%
8 76
 
0.2%
9 73
 
0.2%
16 72
 
0.2%
7 71
 
0.2%
Other values (1012) 15792
50.8%
ValueCountFrequency (%)
0 14424
46.4%
1 61
 
0.2%
2 39
 
0.1%
3 69
 
0.2%
4 154
 
0.5%
5 107
 
0.3%
6 68
 
0.2%
7 71
 
0.2%
8 76
 
0.2%
9 73
 
0.2%
ValueCountFrequency (%)
1024 1
 
< 0.1%
1022 1
 
< 0.1%
1020 4
< 0.1%
1019 1
 
< 0.1%
1018 2
 
< 0.1%
1017 4
< 0.1%
1016 4
< 0.1%
1015 4
< 0.1%
1013 6
< 0.1%
1012 2
 
< 0.1%

cloud_opacity
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct971
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.12881
Minimum0
Maximum97
Zeros559
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:03.887063image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.5
Q132.1
median50.1
Q370.3
95-th percentile92.9
Maximum97
Range97
Interquartile range (IQR)38.2

Descriptive statistics

Standard deviation26.132621
Coefficient of variation (CV)0.52130943
Kurtosis-0.84359185
Mean50.12881
Median Absolute Deviation (MAD)19.1
Skewness-0.094955302
Sum1558003.4
Variance682.9139
MonotonicityNot monotonic
2024-07-25T09:39:03.986743image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 559
 
1.8%
97 110
 
0.4%
96.9 71
 
0.2%
96.8 69
 
0.2%
40.1 68
 
0.2%
37.8 63
 
0.2%
46.1 63
 
0.2%
44.1 63
 
0.2%
47.5 62
 
0.2%
52.7 62
 
0.2%
Other values (961) 29890
96.2%
ValueCountFrequency (%)
0 559
1.8%
0.1 29
 
0.1%
0.2 32
 
0.1%
0.3 33
 
0.1%
0.4 26
 
0.1%
0.5 31
 
0.1%
0.6 29
 
0.1%
0.7 26
 
0.1%
0.8 20
 
0.1%
0.9 18
 
0.1%
ValueCountFrequency (%)
97 110
0.4%
96.9 71
0.2%
96.8 69
0.2%
96.7 43
 
0.1%
96.6 36
 
0.1%
96.5 35
 
0.1%
96.4 30
 
0.1%
96.3 22
 
0.1%
96.2 36
 
0.1%
96.1 38
 
0.1%

dni
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct887
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.31219
Minimum0
Maximum924
Zeros19987
Zeros (%)64.3%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:04.084408image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q392
95-th percentile593
Maximum924
Range924
Interquartile range (IQR)92

Descriptive statistics

Standard deviation196.47962
Coefficient of variation (CV)1.9393481
Kurtosis3.0266585
Mean101.31219
Median Absolute Deviation (MAD)0
Skewness2.0144346
Sum3148783
Variance38604.239
MonotonicityNot monotonic
2024-07-25T09:39:04.183361image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19987
64.3%
1 143
 
0.5%
2 110
 
0.4%
3 109
 
0.4%
5 93
 
0.3%
7 88
 
0.3%
6 86
 
0.3%
4 84
 
0.3%
10 67
 
0.2%
13 64
 
0.2%
Other values (877) 10249
33.0%
ValueCountFrequency (%)
0 19987
64.3%
1 143
 
0.5%
2 110
 
0.4%
3 109
 
0.4%
4 84
 
0.3%
5 93
 
0.3%
6 86
 
0.3%
7 88
 
0.3%
8 62
 
0.2%
9 58
 
0.2%
ValueCountFrequency (%)
924 1
< 0.1%
914 1
< 0.1%
913 1
< 0.1%
909 1
< 0.1%
908 1
< 0.1%
903 1
< 0.1%
898 1
< 0.1%
897 1
< 0.1%
894 2
< 0.1%
893 2
< 0.1%

ghi
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct994
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.26097
Minimum0
Maximum1020
Zeros14473
Zeros (%)46.6%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:04.280167image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q3377
95-th percentile729
Maximum1020
Range1020
Interquartile range (IQR)377

Descriptive statistics

Standard deviation260.54918
Coefficient of variation (CV)1.355185
Kurtosis-0.068249976
Mean192.26097
Median Absolute Deviation (MAD)8
Skewness1.1091107
Sum5975471
Variance67885.875
MonotonicityNot monotonic
2024-07-25T09:39:04.380526image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14473
46.6%
2 188
 
0.6%
3 185
 
0.6%
1 161
 
0.5%
6 145
 
0.5%
5 144
 
0.5%
4 125
 
0.4%
7 112
 
0.4%
8 108
 
0.3%
9 87
 
0.3%
Other values (984) 15352
49.4%
ValueCountFrequency (%)
0 14473
46.6%
1 161
 
0.5%
2 188
 
0.6%
3 185
 
0.6%
4 125
 
0.4%
5 144
 
0.5%
6 145
 
0.5%
7 112
 
0.4%
8 108
 
0.3%
9 87
 
0.3%
ValueCountFrequency (%)
1020 2
< 0.1%
1017 1
< 0.1%
1010 1
< 0.1%
1007 1
< 0.1%
1006 2
< 0.1%
1004 1
< 0.1%
1003 1
< 0.1%
997 1
< 0.1%
992 1
< 0.1%
990 1
< 0.1%

relative_humidity
Real number (ℝ)

HIGH CORRELATION 

Distinct382
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.056641
Minimum54.6
Maximum99.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size242.9 KiB
2024-07-25T09:39:04.477446image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum54.6
5-th percentile71.6
Q179.5
median84.8
Q389.5
95-th percentile93.8
Maximum99.7
Range45.1
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.8821231
Coefficient of variation (CV)0.081874829
Kurtosis-0.17130728
Mean84.056641
Median Absolute Deviation (MAD)4.9
Skewness-0.52657475
Sum2612480.4
Variance47.363619
MonotonicityNot monotonic
2024-07-25T09:39:04.574738image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92.2 297
 
1.0%
92.5 295
 
0.9%
93.6 270
 
0.9%
91.4 269
 
0.9%
91.7 261
 
0.8%
93.3 261
 
0.8%
91.1 260
 
0.8%
87.2 232
 
0.7%
92.8 231
 
0.7%
93.9 231
 
0.7%
Other values (372) 28473
91.6%
ValueCountFrequency (%)
54.6 1
< 0.1%
54.9 2
< 0.1%
55.3 1
< 0.1%
55.4 1
< 0.1%
56.6 1
< 0.1%
57 1
< 0.1%
57.5 1
< 0.1%
58.1 2
< 0.1%
58.3 2
< 0.1%
58.5 1
< 0.1%
ValueCountFrequency (%)
99.7 1
 
< 0.1%
99.1 1
 
< 0.1%
98.8 3
 
< 0.1%
98.5 3
 
< 0.1%
98.2 12
< 0.1%
97.9 8
< 0.1%
97.6 14
< 0.1%
97.4 5
 
< 0.1%
97.3 14
< 0.1%
97.1 11
< 0.1%

period_end
Date

UNIQUE 

Distinct31080
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size242.9 KiB
Minimum2021-01-01 01:00:00+00:00
Maximum2024-07-19 00:00:00+00:00
2024-07-25T09:39:04.675487image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:04.777299image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

year
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
2022
8760 
2023
8760 
2021
8759 
2024
4801 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters124320
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2022 8760
28.2%
2023 8760
28.2%
2021 8759
28.2%
2024 4801
15.4%

Length

2024-07-25T09:39:04.866024image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-25T09:39:04.942269image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
2022 8760
28.2%
2023 8760
28.2%
2021 8759
28.2%
2024 4801
15.4%

Most occurring characters

ValueCountFrequency (%)
2 70920
57.0%
0 31080
25.0%
3 8760
 
7.0%
1 8759
 
7.0%
4 4801
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 124320
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 70920
57.0%
0 31080
25.0%
3 8760
 
7.0%
1 8759
 
7.0%
4 4801
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 124320
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 70920
57.0%
0 31080
25.0%
3 8760
 
7.0%
1 8759
 
7.0%
4 4801
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 124320
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 70920
57.0%
0 31080
25.0%
3 8760
 
7.0%
1 8759
 
7.0%
4 4801
 
3.9%

month
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.107529
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.5 KiB
2024-07-25T09:39:05.015008image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.402419
Coefficient of variation (CV)0.55708601
Kurtosis-1.1373652
Mean6.107529
Median Absolute Deviation (MAD)3
Skewness0.16820227
Sum189822
Variance11.576455
MonotonicityNot monotonic
2024-07-25T09:39:05.402561image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 2976
9.6%
5 2976
9.6%
1 2975
9.6%
4 2880
9.3%
6 2880
9.3%
2 2712
8.7%
7 2665
8.6%
8 2232
7.2%
10 2232
7.2%
12 2232
7.2%
Other values (2) 4320
13.9%
ValueCountFrequency (%)
1 2975
9.6%
2 2712
8.7%
3 2976
9.6%
4 2880
9.3%
5 2976
9.6%
6 2880
9.3%
7 2665
8.6%
8 2232
7.2%
9 2160
6.9%
10 2232
7.2%
ValueCountFrequency (%)
12 2232
7.2%
11 2160
6.9%
10 2232
7.2%
9 2160
6.9%
8 2232
7.2%
7 2665
8.6%
6 2880
9.3%
5 2976
9.6%
4 2880
9.3%
3 2976
9.6%

day
Real number (ℝ)

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.628378
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.5 KiB
2024-07-25T09:39:05.480465image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7821938
Coefficient of variation (CV)0.5619389
Kurtosis-1.1891113
Mean15.628378
Median Absolute Deviation (MAD)8
Skewness0.021490321
Sum485730
Variance77.126927
MonotonicityNot monotonic
2024-07-25T09:39:05.564127image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
16 1032
 
3.3%
10 1032
 
3.3%
2 1032
 
3.3%
15 1032
 
3.3%
14 1032
 
3.3%
13 1032
 
3.3%
12 1032
 
3.3%
11 1032
 
3.3%
9 1032
 
3.3%
18 1032
 
3.3%
Other values (21) 20760
66.8%
ValueCountFrequency (%)
1 1031
3.3%
2 1032
3.3%
3 1032
3.3%
4 1032
3.3%
5 1032
3.3%
6 1032
3.3%
7 1032
3.3%
8 1032
3.3%
9 1032
3.3%
10 1032
3.3%
ValueCountFrequency (%)
31 576
1.9%
30 912
2.9%
29 936
3.0%
28 1008
3.2%
27 1008
3.2%
26 1008
3.2%
25 1008
3.2%
24 1008
3.2%
23 1008
3.2%
22 1008
3.2%

hour
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum0
Maximum23
Zeros1295
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size121.5 KiB
2024-07-25T09:39:05.645960image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15.75
median11.5
Q317.25
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation6.9222979
Coefficient of variation (CV)0.60193895
Kurtosis-1.2041746
Mean11.5
Median Absolute Deviation (MAD)6
Skewness0
Sum357420
Variance47.918208
MonotonicityNot monotonic
2024-07-25T09:39:05.724056image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1295
 
4.2%
2 1295
 
4.2%
23 1295
 
4.2%
22 1295
 
4.2%
21 1295
 
4.2%
20 1295
 
4.2%
19 1295
 
4.2%
18 1295
 
4.2%
17 1295
 
4.2%
16 1295
 
4.2%
Other values (14) 18130
58.3%
ValueCountFrequency (%)
0 1295
4.2%
1 1295
4.2%
2 1295
4.2%
3 1295
4.2%
4 1295
4.2%
5 1295
4.2%
6 1295
4.2%
7 1295
4.2%
8 1295
4.2%
9 1295
4.2%
ValueCountFrequency (%)
23 1295
4.2%
22 1295
4.2%
21 1295
4.2%
20 1295
4.2%
19 1295
4.2%
18 1295
4.2%
17 1295
4.2%
16 1295
4.2%
15 1295
4.2%
14 1295
4.2%

Interactions

2024-07-25T09:39:02.350330image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.570006image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.691389image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.408572image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.077965image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.732874image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.370417image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.037450image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.026522image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.679641image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.411227image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.646654image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.758480image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.474002image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.140047image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.794397image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.432610image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.106810image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.092087image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.745354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.479967image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.719283image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.833967image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.546852image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.213427image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.863821image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.502552image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.185218image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.165583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.819173image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.542752image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.788796image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.903828image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.618675image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.280401image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.927945image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.564706image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.257899image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.233873image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.888154image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.607567image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.856815image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.976049image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.685037image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.347674image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.992103image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.628111image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.605540image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.298874image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.956717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.666532image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.921131image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.048849image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.748237image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.410940image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.051157image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.688182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.672079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.359889image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.019613image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.730236image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:55.986346image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.123310image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.815542image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.475921image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.114076image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.748496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.743274image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.423470image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.085068image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.791455image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.050523image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.196944image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.881552image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.539086image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.181448image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.814603image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.811982image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.483868image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.152311image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.855730image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.116922image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.269736image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.948689image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.603632image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.246383image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.884030image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.884313image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.547390image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.217798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.921304image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:56.184192image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:57.341505image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.015362image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:58.670819image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.308331image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:38:59.968358image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:00.959216image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:01.615649image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-25T09:39:02.287775image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-07-25T09:39:05.784915image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
air_tempclearsky_dhiclearsky_ghicloud_opacitydaydnighihourmonthrelative_humidityyear
air_temp1.0000.6100.640-0.4530.0180.5460.6480.463-0.159-0.6520.227
clearsky_dhi0.6101.0000.968-0.593-0.0010.7050.9520.784-0.008-0.5720.056
clearsky_ghi0.6400.9681.000-0.602-0.0000.7300.9760.784-0.013-0.5910.025
cloud_opacity-0.453-0.593-0.6021.0000.017-0.810-0.704-0.526-0.0670.4970.040
day0.018-0.001-0.0000.0171.0000.0010.001-0.0000.0070.0040.000
dni0.5460.7050.730-0.8100.0011.0000.8340.658-0.000-0.5080.036
ghi0.6480.9520.976-0.7040.0010.8341.0000.789-0.010-0.5990.028
hour0.4630.7840.784-0.526-0.0000.6580.7891.000-0.000-0.4140.000
month-0.159-0.008-0.013-0.0670.007-0.000-0.010-0.0001.000-0.2670.186
relative_humidity-0.652-0.572-0.5910.4970.004-0.508-0.599-0.414-0.2671.0000.095
year0.2270.0560.0250.0400.0000.0360.0280.0000.1860.0951.000

Missing values

2024-07-25T09:39:03.009270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-25T09:39:03.153519image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

air_tempclearsky_dhiclearsky_ghicloud_opacitydnighirelative_humidityperiod_endyearmonthdayhour
0250086.60082.42021-01-01 01:00:00+00:002021111
1250065.00082.92021-01-01 02:00:00+00:002021112
2240065.10083.12021-01-01 03:00:00+00:002021113
3240052.70082.82021-01-01 04:00:00+00:002021114
4240054.70083.12021-01-01 05:00:00+00:002021115
5240059.90083.32021-01-01 06:00:00+00:002021116
6240072.00083.62021-01-01 07:00:00+00:002021117
7240053.30084.12021-01-01 08:00:00+00:002021118
8240075.40084.42021-01-01 09:00:00+00:002021119
9240081.20084.62021-01-01 10:00:00+00:0020211110
air_tempclearsky_dhiclearsky_ghicloud_opacitydnighirelative_humidityperiod_endyearmonthdayhour
310702511461610.051955080.22024-07-18 15:00:00+00:00202471815
310712512277531.413353178.12024-07-18 16:00:00+00:00202471816
310722612987318.638971278.32024-07-18 17:00:00+00:00202471817
310732512890416.543475479.32024-07-18 18:00:00+00:00202471818
31074261258637.463679978.82024-07-18 19:00:00+00:00202471819
31075261217533.271072978.42024-07-18 20:00:00+00:00202471820
31076261125856.258654778.62024-07-18 21:00:00+00:00202471821
3107725963765.550135479.32024-07-18 22:00:00+00:00202471822
31078256115410.424314181.22024-07-18 23:00:00+00:00202471823
310792481039.02883.62024-07-19 00:00:00+00:0020247190